A class of effect size indices are discussed that evaluate the degree to which two nested confirmatory factor analysis models differ from each other in terms of fit to a set of observed variables. These descriptive effect measures can be used to quantify the impact of parameter restrictions imposed in an initially considered model and are free…

Researchers often study dynamic processes of latent variables in everyday life, such as the interplay of positive and negative affect over time. An intuitive approach is to first estimate the measurement model of the latent variables, then compute factor scores, and finally use these factor scores as observed scores in vector autoregressive…

This work proposes simple experiments to introduce some fundamental concepts of the measurement area. It associates theory and practice through a strategy where the students create a real temperature data set with an Arduino board and three LM35DZ sensors and later use mathematical software to identify theoretical concepts as measurement accuracy…

As the field of chemistry education moves toward greater inclusion and increased participation by underrepresented minorities, standards for investigating the differential impacts and outcomes of learning environments have to be considered. While quantitative methods may not be capable of generating the in-depth nuances of qualitative methods,…

This article outlines a procedure for examining the degree to which a common factor may be dominating additional factors in a multicomponent measuring instrument consisting of binary items. The procedure rests on an application of the latent variable modeling methodology and accounts for the discrete nature of the manifest indicators. The method…

This study compared five common multilevel software packages via Monte Carlo simulation: HLM 7, M"plus" 7.4, R (lme4 V1.1-12), Stata 14.1, and SAS 9.4 to determine how the programs differ in estimation accuracy and speed, as well as convergence, when modeling multiple randomly varying slopes of different magnitudes. Simulated data…

In comparing measurement theories, it is evident that the awareness of the concept of measurement error during the time of Galileo has lead to the formulation of observed scores comprising a true score and error (classical theory), universe score and various random error components (generalizability theory), or individual latent ability and error…

The crux in psychometrics is how to estimate the probability that a respondent answers an item correctly on one occasion out of many. Under the current testing paradigm this probability is estimated using all kinds of statistical techniques and mathematical modeling. Multiple evaluation is a new testing paradigm using the person's own personal…

Some specific computer-based tools for collecting and examining audit trails, i.e., data that describe a learner's path through a computer-based instruction (CBI) lesson, are detailed. Data analysis and measurement issues related to audit trails are also discussed. A particular set of embedded computer-based tools currently being used at San Diego…

LISREL-type structural equation modeling is a powerful statistical technique that seems appropriate for social science variables which are complex and difficult to measure. The literature on the specification, estimation, and testing of such models is voluminous. The greatest proportion of this literature, however, focuses on the technical aspects…

The advantages of applying confirmatory factor analysis (CFA) to multitrait-multimethod (MTMM) data are widely recognized. However, because CFA as traditionally applied to MTMM data incorporates single indicators of each scale (i.e., each trait/method combination), important weaknesses are the failure to: (1) correct appropriately for measurement…